{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "similar-durham",
   "metadata": {},
   "source": [
    "# `geomFunction()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "aware-wellington",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"cgNsLg\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"library\">\n",
       "       if(!window.letsPlotCallQueue) {\n",
       "           window.letsPlotCallQueue = [];\n",
       "       }; \n",
       "       window.letsPlotCall = function(f) {\n",
       "           window.letsPlotCallQueue.push(f);\n",
       "       };\n",
       "       (function() {\n",
       "           var script = document.createElement(\"script\");\n",
       "           script.type = \"text/javascript\";\n",
       "           script.src = \"https://cdn.jsdelivr.net/gh/JetBrains/lets-plot@v4.0.0/js-package/distr/lets-plot.min.js\";\n",
       "           script.onload = function() {\n",
       "               window.letsPlotCall = function(f) {f();};\n",
       "               window.letsPlotCallQueue.forEach(function(f) {f();});\n",
       "               window.letsPlotCallQueue = [];\n",
       "               \n",
       "               \n",
       "           };\n",
       "           script.onerror = function(event) {\n",
       "               window.letsPlotCall = function(f) {};\n",
       "               window.letsPlotCallQueue = [];\n",
       "               var div = document.createElement(\"div\");\n",
       "               div.style.color = 'darkred';\n",
       "               div.textContent = 'Error loading Lets-Plot JS';\n",
       "               document.getElementById(\"cgNsLg\").appendChild(div);\n",
       "           };\n",
       "           var e = document.getElementById(\"cgNsLg\");\n",
       "           e.appendChild(script);\n",
       "       })();\n",
       "   </script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "            <div id=\"kotlin_out_0\"/>\n",
       "            <script type=\"text/javascript\">\n",
       "                            if(!window.kotlinQueues) {\n",
       "                window.kotlinQueues = {};\n",
       "            }\n",
       "            if(!window.kotlinQueues[\"DataFrame\"]) {\n",
       "                var resQueue = [];\n",
       "                window.kotlinQueues[\"DataFrame\"] = resQueue;\n",
       "                window[\"call_DataFrame\"] = function(f) {\n",
       "                    resQueue.push(f);\n",
       "                }\n",
       "            }\n",
       "            (function (){\n",
       "                var modifiers = [(function(script) {\n",
       "    script.src = \"https://cdn.jsdelivr.net/gh/Kotlin/dataframe@3db46ccccaa1291c0627307d64133317f545e6ae/core/src/main/resources/init.js\"\n",
       "    script.type = \"text/javascript\";\n",
       "})];\n",
       "                var e = document.getElementById(\"kotlin_out_0\");\n",
       "                modifiers.forEach(function (gen) {\n",
       "                    var script = document.createElement(\"script\");\n",
       "                    gen(script)\n",
       "                    script.addEventListener(\"load\", function() {\n",
       "                        window[\"call_DataFrame\"] = function(f) {f();};\n",
       "                        window.kotlinQueues[\"DataFrame\"].forEach(function(f) {f();});\n",
       "                        window.kotlinQueues[\"DataFrame\"] = [];\n",
       "                    }, false);\n",
       "                    script.addEventListener(\"error\", function() {\n",
       "                        window[\"call_DataFrame\"] = function(f) {};\n",
       "                        window.kotlinQueues[\"DataFrame\"] = [];\n",
       "                        var div = document.createElement(\"div\");\n",
       "                        div.style.color = 'darkred';\n",
       "                        div.textContent = 'Error loading resource DataFrame';\n",
       "                        document.getElementById(\"kotlin_out_0\").appendChild(div);\n",
       "                    }, false);\n",
       "                    \n",
       "                    e.appendChild(script);\n",
       "                });\n",
       "            })();\n",
       "            </script>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "                <style>\n",
       "                :root {\n",
       "    --background: #fff;\n",
       "    --background-odd: #f5f5f5;\n",
       "    --background-hover: #d9edfd;\n",
       "    --header-text-color: #474747;\n",
       "    --text-color: #848484;\n",
       "    --text-color-dark: #000;\n",
       "    --text-color-medium: #737373;\n",
       "    --text-color-pale: #b3b3b3;\n",
       "    --inner-border-color: #aaa;\n",
       "    --bold-border-color: #000;\n",
       "    --link-color: #296eaa;\n",
       "    --link-color-pale: #296eaa;\n",
       "    --link-hover: #1a466c;\n",
       "}\n",
       "\n",
       ":root[theme=\"dark\"], :root [data-jp-theme-light=\"false\"], .dataframe_dark{\n",
       "    --background: #303030;\n",
       "    --background-odd: #3c3c3c;\n",
       "    --background-hover: #464646;\n",
       "    --header-text-color: #dddddd;\n",
       "    --text-color: #b3b3b3;\n",
       "    --text-color-dark: #dddddd;\n",
       "    --text-color-medium: #b2b2b2;\n",
       "    --text-color-pale: #737373;\n",
       "    --inner-border-color: #707070;\n",
       "    --bold-border-color: #777777;\n",
       "    --link-color: #008dc0;\n",
       "    --link-color-pale: #97e1fb;\n",
       "    --link-hover: #00688e;\n",
       "}\n",
       "\n",
       "p.dataframe_description {\n",
       "    color: var(--text-color-dark);\n",
       "}\n",
       "\n",
       "table.dataframe {\n",
       "    font-family: \"Helvetica Neue\", Helvetica, Arial, sans-serif;\n",
       "    font-size: 12px;\n",
       "    background-color: var(--background);\n",
       "    color: var(--text-color-dark);\n",
       "    border: none;\n",
       "    border-collapse: collapse;\n",
       "}\n",
       "\n",
       "table.dataframe th, td {\n",
       "    padding: 6px;\n",
       "    border: 1px solid transparent;\n",
       "    text-align: left;\n",
       "}\n",
       "\n",
       "table.dataframe th {\n",
       "    background-color: var(--background);\n",
       "    color: var(--header-text-color);\n",
       "}\n",
       "\n",
       "table.dataframe td {\n",
       "    vertical-align: top;\n",
       "}\n",
       "\n",
       "table.dataframe th.bottomBorder {\n",
       "    border-bottom-color: var(--bold-border-color);\n",
       "}\n",
       "\n",
       "table.dataframe tbody > tr:nth-child(odd) {\n",
       "    background: var(--background-odd);\n",
       "}\n",
       "\n",
       "table.dataframe tbody > tr:nth-child(even) {\n",
       "    background: var(--background);\n",
       "}\n",
       "\n",
       "table.dataframe tbody > tr:hover {\n",
       "    background: var(--background-hover);\n",
       "}\n",
       "\n",
       "table.dataframe a {\n",
       "    cursor: pointer;\n",
       "    color: var(--link-color);\n",
       "    text-decoration: none;\n",
       "}\n",
       "\n",
       "table.dataframe tr:hover > td a {\n",
       "    color: var(--link-color-pale);\n",
       "}\n",
       "\n",
       "table.dataframe a:hover {\n",
       "    color: var(--link-hover);\n",
       "    text-decoration: underline;\n",
       "}\n",
       "\n",
       "table.dataframe img {\n",
       "    max-width: fit-content;\n",
       "}\n",
       "\n",
       "table.dataframe th.complex {\n",
       "    background-color: var(--background);\n",
       "    border: 1px solid var(--background);\n",
       "}\n",
       "\n",
       "table.dataframe .leftBorder {\n",
       "    border-left-color: var(--inner-border-color);\n",
       "}\n",
       "\n",
       "table.dataframe .rightBorder {\n",
       "    border-right-color: var(--inner-border-color);\n",
       "}\n",
       "\n",
       "table.dataframe .rightAlign {\n",
       "    text-align: right;\n",
       "}\n",
       "\n",
       "table.dataframe .expanderSvg {\n",
       "    width: 8px;\n",
       "    height: 8px;\n",
       "    margin-right: 3px;\n",
       "}\n",
       "\n",
       "table.dataframe .expander {\n",
       "    display: flex;\n",
       "    align-items: center;\n",
       "}\n",
       "\n",
       "/* formatting */\n",
       "\n",
       "table.dataframe .null {\n",
       "    color: var(--text-color-pale);\n",
       "}\n",
       "\n",
       "table.dataframe .structural {\n",
       "    color: var(--text-color-medium);\n",
       "    font-weight: bold;\n",
       "}\n",
       "\n",
       "table.dataframe .dataFrameCaption {\n",
       "    font-weight: bold;\n",
       "}\n",
       "\n",
       "table.dataframe .numbers {\n",
       "    color: var(--text-color-dark);\n",
       "}\n",
       "\n",
       "table.dataframe td:hover .formatted .structural, .null {\n",
       "    color: var(--text-color-dark);\n",
       "}\n",
       "\n",
       "table.dataframe tr:hover .formatted .structural, .null {\n",
       "    color: var(--text-color-dark);\n",
       "}\n",
       "\n",
       "\n",
       "                </style>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%useLatestDescriptors\n",
    "%use lets-plot\n",
    "%use dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "floppy-techno",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Lets-Plot Kotlin API v.4.4.2. Frontend: Notebook with dynamically loaded JS. Lets-Plot JS v.4.0.0."
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "LetsPlot.getInfo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "dimensional-disclosure",
   "metadata": {},
   "outputs": [],
   "source": [
    "import java.util.*\n",
    "\n",
    "val ran: Random = Random(37)\n",
    "val norm: ((Double) -> Double)? = {ran.nextGaussian()}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "instant-keyboard",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"hRYCWG\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
       "\"mapping\":{\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "\"x\":\"x\",\n",
       "\"y\":\"y\"\n",
       "},\n",
       "\"stat\":\"identity\",\n",
       "\"data\":{\n",
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       "           var plotContainer = document.getElementById(\"hRYCWG\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
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      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "letsPlot() + geomFunction(fn = norm, xlim = Pair(-3, 3), geom=Geom.point())"
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  {
   "cell_type": "markdown",
   "id": "assigned-turtle",
   "metadata": {},
   "source": [
    "### 1. Comparison With Empirical Density"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "plastic-witch",
   "metadata": {},
   "outputs": [
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       "{ name: \"<span title=\\\"displ: Double\\\">displ</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1.8</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1.8</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">2.0</span></span>\"] }, \n",
       "{ name: \"<span title=\\\"year: Int\\\">year</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1999</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">1999</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">2008</span></span>\"] }, \n",
       "{ name: \"<span title=\\\"cyl: Int\\\">cyl</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">4</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">4</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">4</span></span>\"] }, \n",
       "{ name: \"<span title=\\\"trans: String\\\">trans</span>\", children: [], rightAlign: false, values: [\"auto(l5)\",\"manual(m5)\",\"manual(m6)\"] }, \n",
       "{ name: \"<span title=\\\"drv: String\\\">drv</span>\", children: [], rightAlign: false, values: [\"f\",\"f\",\"f\"] }, \n",
       "{ name: \"<span title=\\\"cty: Int\\\">cty</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">18</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">21</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">20</span></span>\"] }, \n",
       "{ name: \"<span title=\\\"hwy: Int\\\">hwy</span>\", children: [], rightAlign: true, values: [\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">29</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">29</span></span>\",\"<span class=\\\"formatted\\\" title=\\\"\\\"><span class=\\\"numbers\\\">31</span></span>\"] }, \n",
       "{ name: \"<span title=\\\"fl: String\\\">fl</span>\", children: [], rightAlign: false, values: [\"p\",\"p\",\"p\"] }, \n",
       "{ name: \"<span title=\\\"class: String\\\">class</span>\", children: [], rightAlign: false, values: [\"compact\",\"compact\",\"compact\"] }, \n",
       "], id: -855638016, rootId: -855638016, totalRows: 3 } ) });\n",
       "/*-->*/\n",
       "\n",
       "call_DataFrame(function() { DataFrame.renderTable(-855638016) });\n",
       "\n",
       "\n",
       "        </script>\n",
       "        </html>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "val mpg = DataFrame.readCSV(\"https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/mpg.csv\")\n",
    "mpg.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "wooden-pipeline",
   "metadata": {},
   "outputs": [],
   "source": [
    "val mpgData = mpg.toMap()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "voluntary-acrobat",
   "metadata": {},
   "outputs": [],
   "source": [
    "import org.jetbrains.letsPlot.core.plot.base.stat.math3.NormalDistribution\n",
    "\n",
    "val loc = mpg.cty.mean()\n",
    "val scale = mpg.cty.std()\n",
    "val xmin = mpg.cty.min()\n",
    "val xmax = mpg.cty.max()\n",
    "\n",
    "val normalDistribution = NormalDistribution(loc, scale)\n",
    "val func : (Double) -> Double = { t -> normalDistribution.density(t) }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "sacred-harvard",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\"stat\":\"density\",\n",
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       "\"geom\":\"density\",\n",
       "\"data\":{\n",
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       "},\n",
       "\"color\":\"red\",\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"line\"\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"trJKTw\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "letsPlot(mpgData) { x = \"cty\" } +\n",
    "    geomDensity() +\n",
    "    geomFunction(fn = func, xlim = xmin to xmax, color = \"red\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "hourly-commonwealth",
   "metadata": {},
   "source": [
    "### 2. Use Data to Autodetect `xlim`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "posted-diabetes",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"hANjFX\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
       "\"mapping\":{\n",
       "\"x\":\"cty\"\n",
       "},\n",
       "\"data\":{\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "},\n",
       "\"stat\":\"density\",\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"density\",\n",
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       "\"cty\":[18.0,21.0,20.0,21.0,16.0,18.0,18.0,18.0,16.0,20.0,19.0,15.0,17.0,17.0,15.0,15.0,17.0,16.0,14.0,11.0,14.0,13.0,12.0,16.0,15.0,16.0,15.0,15.0,14.0,11.0,11.0,14.0,19.0,22.0,18.0,18.0,17.0,18.0,17.0,16.0,16.0,17.0,17.0,11.0,15.0,15.0,16.0,16.0,15.0,14.0,13.0,14.0,14.0,14.0,9.0,11.0,11.0,13.0,13.0,9.0,13.0,11.0,13.0,11.0,12.0,9.0,13.0,13.0,12.0,9.0,11.0,11.0,13.0,11.0,11.0,11.0,12.0,14.0,15.0,14.0,13.0,13.0,13.0,14.0,14.0,13.0,13.0,13.0,11.0,13.0,18.0,18.0,17.0,16.0,15.0,15.0,15.0,15.0,14.0,28.0,24.0,25.0,23.0,24.0,26.0,25.0,24.0,21.0,18.0,18.0,21.0,21.0,18.0,18.0,19.0,19.0,19.0,20.0,20.0,17.0,16.0,17.0,17.0,15.0,15.0,14.0,9.0,14.0,13.0,11.0,11.0,12.0,12.0,11.0,11.0,11.0,12.0,14.0,13.0,13.0,13.0,21.0,19.0,23.0,23.0,19.0,19.0,18.0,19.0,19.0,14.0,15.0,14.0,12.0,18.0,16.0,17.0,18.0,16.0,18.0,18.0,20.0,19.0,20.0,18.0,21.0,19.0,19.0,19.0,20.0,20.0,19.0,20.0,15.0,16.0,15.0,15.0,16.0,14.0,21.0,21.0,21.0,21.0,18.0,18.0,19.0,21.0,21.0,21.0,22.0,18.0,18.0,18.0,24.0,24.0,26.0,28.0,26.0,11.0,13.0,15.0,16.0,17.0,15.0,15.0,15.0,16.0,21.0,19.0,21.0,22.0,17.0,33.0,21.0,19.0,22.0,21.0,21.0,21.0,16.0,17.0,35.0,29.0,21.0,19.0,20.0,20.0,21.0,18.0,19.0,21.0,16.0,18.0,17.0]\n",
       "},\n",
       "\"color\":\"red\",\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"line\"\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"hANjFX\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "letsPlot(mpgData) { x = \"cty\" } +\n",
    "    geomDensity() +\n",
    "    geomFunction(data = mpgData, fn = func, xlim = xmin to xmax, color = \"red\") { x = \"cty\" }"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "exempt-twist",
   "metadata": {},
   "source": [
    "### 3. Composition of Function and Statistic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "painful-inside",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"1skaYP\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
       "\"mapping\":{\n",
       "\"x\":\"cty\"\n",
       "},\n",
       "\"data\":{\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "},\n",
       "\"stat\":\"density\",\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"density\",\n",
       "\"data\":{\n",
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       "},\n",
       "\"method\":\"loess\",\n",
       "\"color\":\"red\",\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"line\",\n",
       "\"span\":0.3\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"1skaYP\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "letsPlot(mpgData) { x = \"cty\" } +\n",
    "    geomDensity() +\n",
    "    geomFunction(\n",
    "        fn = func, \n",
    "        xlim = xmin to xmax,\n",
    "        stat = Stat.smooth( \n",
    "            method = \"loess\", \n",
    "            span = 0.3\n",
    "        ),\n",
    "        color = \"red\"\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "pediatric-spoke",
   "metadata": {},
   "source": [
    "### 4. Use Different Geometry"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "criminal-longer",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "   <div id=\"4gWW2h\"></div>\n",
       "   <script type=\"text/javascript\" data-lets-plot-script=\"plot\">\n",
       "       (function() {\n",
       "           var plotSpec={\n",
       "\"mapping\":{\n",
       "\"x\":\"cty\"\n",
       "},\n",
       "\"data\":{\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[{\n",
       "\"aesthetic\":\"fill\",\n",
       "\"scale_mapper_kind\":\"color_brewer\",\n",
       "\"palette\":\"YlOrRd\",\n",
       "\"type\":\"seq\",\n",
       "\"trans\":\"reverse\"\n",
       "}],\n",
       "\"layers\":[{\n",
       "\"mapping\":{\n",
       "},\n",
       "\"stat\":\"density\",\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"density\",\n",
       "\"data\":{\n",
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       "},\n",
       "\"alpha\":0.5,\n",
       "\"position\":\"identity\",\n",
       "\"geom\":\"histogram\"\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"4gWW2h\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();    \n",
       "   </script>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "letsPlot(mpgData) { x = \"cty\" } +\n",
    "    geomDensity() +\n",
    "    geomFunction(\n",
    "        fn = func, \n",
    "        xlim = xmin to xmax,\n",
    "        n = 30,\n",
    "        geom = Geom.histogram() { fill = \"y\" },\n",
    "        alpha = 0.5\n",
    "    ) +\n",
    "    scaleFillBrewer(type = \"seq\", palette = \"YlOrRd\", trans = \"reverse\")"
   ]
  }
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